Energy Efficiency for WiFi and Short Video

Principal Investigator: Dr. Striegel, Department of Computer Science and Engineering

Project Summary:

Short video services such as TikTok, Instagram Reels, and YouTube Shorts are a significant consumer of network bandwidth on WiFi networks. Generally, solutions towards meeting this consumption has trended towards improved WiFi speeds leveraging higher frequencies such as 6 GHz and wider channel widths. However, there have been only limited explorations looking at the energy efficiency of transferring content such as short video where the content can be adaptive to different bit rates and impacts on the network. The focus of this project will be to examine the Power Profiler offered by ODPM in Android, various short video apps, and differing WiFi modalities to begin to understand the energy impact on not only that device but also other network users.

Student’s Role:

The ideal student will have reasonable experience in a programming language such as Python, Java, or C and a willingness to learn and explore the Android development environment. The student will work closely with students from Prof. Striegel and Prof. Ghosh’s groups to conduct the various explorations using recent Pixel phone variants.